Evidence map›Paper›PMID 30370722›Full record

ReviewSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2018

[Research progress about brain-computer interface technology based on cognitive brain areas and its applications in rehabilitation].

Huilin Zhou, Jialin Xu, Changcheng Shi, Guokun Zuo

Abstract readEnglish AbstractReview
In one paragraph

Review in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Huilin ZhouNingbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang 315201, P.R.China;University of Chinese Academy of Sciences, Beijing 100049, P.R.China.
Jialin XuNingbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang 315201, P.R.China.
Changcheng ShiNingbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang 315201, P.R.China.
Guokun ZuoNingbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang 315201, P.R.China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain-computer interface (BCI) technology enable humans to interact with external devices by decoding their brain signals. Despite it has made some significant breakthroughs in recent years, there are still many obstacles in its applications and extensions. The current used BCI control signals are generally derived from the brain areas involved in primary sensory- or motor-related processing. However, these signals only reflect a limited range of limb movement intention. Therefore, additional sources of brain signals for controlling BCI systems need to be explored. Brain signals derived from the cognitive brain areas are more intuitive and effective. These signals can be used for expand the brain signal sources as a new approach. This paper reviewed the research status of cognitive BCI based on the single brain area and multiple hybrid brain areas, and summarized its applications in the rehabilitation medicine. It's believed that cognitive BCI technologies would become a possible breakthrough for future BCI rehabilitation applications.

Indexed as

brain-computer interfacecognitive brain signalsmultiple hybrid brain areasrehabilitation medicinesingle brain area

Identifiers

PMID30370722
PMCPMC9935251

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.